A roadmap for AI policy questions

Robot law pioneer Ryan Calo (previously) has published a "roadmap" for an "artificial intelligence policy...to help policymakers, investors, technologists, scholars, and students understand the contemporary policy environment around AI at least well enough to initiative their own exploration." Read the rest

"Adversarial perturbations" reliably trick AIs about what kind of road-sign they're seeing

An "adversarial perturbation" is a change to a physical object that is deliberately designed to fool a machine-learning system into mistaking it for something else. Read the rest

British place-names generated by a neural net

Dan Hon (perfecting earlier work by Tom Taylor) trained an AI on the vast corpus of British place names, then set it loose. The results are amazing, illustrative of an uncannily human humor seemingly at work, something you'd never get from the standard syllable-randomizing place name generators of yore.

"There aren’t as many cocks as you’d think," he writes.

My favorites: Brotters Common, Boll of Binclestead, Farton Green Pear End, Weston Parpenham, Sutsy Compton, Stoke of Inch, Kinindworthorpe Marmile, Rastan-on-croan, Fuckley, Fapton, Waterwitherwell.

See also Hon's AI trained to generate Ask Metafilter post titles.

Surely neural-net-generated Liffs are next. Read the rest

Big data + private health insurance = game over

Once big data systems agglomerate enough data about you to predict whether you are likely to get sick or badly injured, insurers will be able to deny coverage (or charge so much for it that it amounts to the same thing) to anyone who is likely to get sick, forcing everyone who might ever need insurance into medical bankruptcy, and turning Medicaid into a giant "high-risk pool" that taxpayers foot the bill for. Read the rest

Chinese State Council Guidelines for Artificial Intelligence

The Chinese government's wish-list for AI researchers is pretty ambitious: "Breakthroughs should be made in basic theories of AI, such as big data intelligence, multimedia aware computing, human-machine hybrid intelligence, swarm intelligence and automated decision-making." Read the rest

Techniques for reliably fooling AI machine-vision classifiers

The Open AI researchers were intrigued by a claim that self-driving cars would be intrinsically hard to fool (tricking them into sudden braking maneuvers, say), because "they capture images from multiple scales, angles, perspectives, and the like." Read the rest

AI paint color names improving, sort of

The AI paint name generator (previously) has refined its preferences. Though still very bad at naming paint colors, there seems to be (to my mind) an emerging personality, one that has beliefs and, perhaps, opinions about its creators.

Pictured at the top of this post, for reference, is the human-named classic Opaque Couché.

Latest experiments reveal AI is still terrible at naming paint colors [Ars Technica] Read the rest

How one Lego reseller built an artificial intelligence to sort bricks

Jacques Mattheij hoped to make some cash buying cheap boxes of used, unsorted Lego that he'd organize into more valuable assortments for resale. After acquiring two metric tons of bricks, he was motivated to build a technological solution for sorting. He outfitted a conveyor belt with a cheap magnifying USB camera and employed air nozzles to blow the bricks into various bins. The bigger challenge though was how to get the PC to identify the bricks. From IEEE Spectrum:

After a few other failed approaches, and six months in, I decided to try out a neural network. I settled on using TensorFlow, an immense library produced by the Google Brain Team. TensorFlow can run on a CPU, but for a huge speed increase I tapped the parallel computing power of the graphics processing unit in my US $700 GTX1080 Ti Nvidia video card....

...I managed to label a starter set of about 500 assorted scanned pieces. Using those parts to train the net, the next day the machine sorted 2,000 more parts. About half of those were wrongly labeled, which I corrected. The resulting 2,500 parts were the basis for the next round of training. Another 4,000 parts went through the machine, 90 percent of which were labeled correctly! So, I had to correct only some 400 parts. By the end of two weeks I had a training data set of 20,000 correctly labeled images...

Once the software is able to reliably classify across the entire range of parts in my garage, I’ll be pushing through the remainder of those two tons of bricks.

Read the rest

Machine vision framework wants you to put down your weapon

This is doing the viral rounds described as a Google technology, but it's actually Apple's VisionCore in action. It runs offline on the local device, requiring no number-crunching help from the cloud. Here's a breakdown of how it identifies things through code.

You will need the beta version of xCode and a device running the iOS 11 beta (make sure you only install the beta software on a test device!).

I liked watching it contemplate whether a metal ruler was a meat cleaver or a "chopper." Whispers of the ACLU lawsuits of tomorrow: I think you'd better do what he says, Mr. Kinney. Read the rest

Pictures of dinosaurs, by a flower-drawing algorithm

Chris Rodley fed some pictures of dinosaurs to a "style transfer" machine-learning system that had been trained to draw flowers, and this was the gorgeous result. (via Kottke) Read the rest

Algorithmic decision-making: an arms-race between entropy, programmers and referees

Nesta's Juan Mateos-Garcia proposes that "entropic forces" make algorithmic decision-making tools worse over time, requiring that they be continuously maintained and improved (this is also a key idea from Cathy O'Neil's Weapons of Math Destruction: a machine-learning system is only honest if someone is continuously matching its predictions to reality and refining its model based on the mistakes it makes). Read the rest

Stephen Wolfram's "A New Kind of Science" goes open-access

It's been 15 years since the publication of Steven Wolfram's A New Kind of Science, a mindblowing, back-breaking 1,200-page book that (sort of) says the whole universe is made up of recursive fractals, also noteworthy for the frequent repetition of the phrase "A new kind of science" in its early chapters. Read the rest

Entrancing avant-garde music video generated by algorithm

Damien Henry, co-inventor of Google Cardboard, trained a machine learning algorithm using footage shot from a moving vehicle and then had the machine generate this beautiful video.

"Graphics are 100% generated by an algorithm in one shot. No edit or post-processing," Henry writes. "Except the first one, all frames are calculated one by one by a prediction algorithm that tries to predict the next frame from the previous one."

The soundtrack is the Steve Reich masterpiece "Music for 18 Musicians."

Read the rest

The weird poetry Google Translate writes when fed the same characters over and over

@Smutclyde Google Translated sequences of unicode characters and short pairings, at varying lengths, to see what the neural networks would interpret each as. The results are remarkable. Lovecraftian wailings, for example, become homoerotic death metal lyrics. And is this not as disturbing as it is funny? Especially when you consider that the machine minds are learning their way beyond our comprehension. Read the rest

Kevin Kelly: "superhuman" AI is bullshit

Kevin Kelly argues that the core premises that underlie the belief that artificial intelligence will overtake human intelligence are "more akin to a religious belief — a myth" than a scientific theory. Read the rest

The next iteration of Alexa is designed to watch you while you get dressed

The Echo Look is the next version of the Alexa appliance: it has an camera hooked up to a computer vision system, along with its always-on mic, and the first application for it is to watch you as you dress and give you fashion advice (that is, recommend clothes you can order from Amazon). Read the rest

Scientists ponder the possibility of quantum consciousness

As AI improves, the mystery of consciousness interests more programmers and physicists. Read the rest

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